cleanup, cob ladder still broken

NN/models/dqn_agent.py

@@ -113,6 +113,15 @@ class DQNAgent:
         # Initialize avg_reward for dashboard compatibility
         self.avg_reward = 0.0  # Average reward tracking for dashboard
         
+        # Market regime adaptation weights
+        self.market_regime_weights = {
+            'trending': 1.0,
+            'sideways': 0.8,
+            'volatile': 1.2,
+            'bullish': 1.1,
+            'bearish': 1.1
+        }
+        
         # Load best checkpoint if available
         if self.enable_checkpoints:
             self.load_best_checkpoint()
@@ -490,7 +499,17 @@ class DQNAgent:
             state_tensor = torch.FloatTensor(state).unsqueeze(0).to(self.device)
             q_values = self.policy_net(state_tensor)
             
-            # Ensure q_values has correct shape for softmax
+            # Handle case where network might return a tuple instead of tensor
+            if isinstance(q_values, tuple):
+                # If it's a tuple, take the first element (usually the main output)
+                q_values = q_values[0]
+            
+            # Ensure q_values is a tensor and has correct shape for softmax
+            if not hasattr(q_values, 'dim'):
+                logger.error(f"DQN: q_values is not a tensor: {type(q_values)}")
+                # Return default action with low confidence
+                return 1, 0.1  # Default to HOLD action
+            
             if q_values.dim() == 1:
                 q_values = q_values.unsqueeze(0)